Electrical systems for various equipment and buildings, particularly commercial and industrial electrical systems use large quantities of electrical power. For example, commercial buildings use a significant amount of energy as part of their day-to-day operations. It is estimated that commercial buildings in the United States alone consumed an estimated 37% of the total electricity generated in the United States. The electricity cost for a building operator or tenant of a building is one of the largest costs associated with the building. The two primary uses of electricity in commercial buildings are generally related to lighting and climate control or HVAC.
To reduce energy consumption and avoid unnecessary expense, operators of electrical systems attempt to be more energy efficient. For example, building managers employ a variety of methods and devices to estimate building occupancy, such as timers and motion detectors, and therefore reduce energy use. To avoid turning off or reducing services while the building is occupied, timers are typically configured to reduce lighting and climate control well before or well after a building is occupied, which minimizes their effectiveness at reducing energy consumption on a day-to-day basis. In addition, timers are incapable of adjusting for floating holidays or other periods of abnormal low building occupancy, unless specifically programmed by the operator. Motion detectors solve many of the problems associated with timers, but are very expensive to install throughout a building and interconnect with a controller, particularly in existing buildings. However, none of these models identify anomalies in the energy consumption of the building, especially real time identification of anomalies.
Many utilities are installing smart meters in electrical systems to measure power attributes, such as voltage, current, power, or any other desirable characteristic. While all of these meters may record real time energy usage, it is very difficult for an operator to inspect all of the power related data that is collected, particularly in real time or as close to real time as possible to detect anomalies in power consumption. Typically, it is labor-intensive and therefore an expensive procedure for an electrical system operator, such as a building administrator, to meticulously go through the vast amount of power data. Thus, many equipment anomalies and changes in usage patterns that affect the power consumption of a device or appliance but do not negatively affect the performance remain undetected. While computers are well suited to handle volumes of data that a building administrator cannot, there are still challenges. The first challenge is the lack of labeled data to train an algorithm for detecting anomalous behavior. Obtaining labeled data is an expensive procedure as it usually requires extensive human interaction.